Data Collection and Analysis in SociolinguisticsPractical elements for research methods in sociolinguistics

Enrico GiaiBA in Translating and InterpretingMA Student in Translation Studies Turin University

Email: enrico.giai@gmail.com

Turin, 07-08 April 2014

2 Tuesday, April 8th

Main topics Inferential statistics

Variables Hypothesis Null Hypothesis Likelihood Chi square test ANOVA

Rbrul for inferential and multivariate statistics

3 Inferential Statistics –Variables Two types of variables

Dependent Independent

The independent variable(s) affect the dependent variable in some predictable way

Another classification (for questions): Category type variables (usually dependent variables) Ordinal type variables Continuous type variables (usually independent variables)

4 Inferential Statistics –Experimental and Null Hypothesis Experimental hypothesis

The hypothesis according to which a certain variable is affected in a predictable & systematic way by some other variable

Must be tested

Null hypothesis: the exact opposite of the experimental hypothesis

5 Inferential Statistics –Likelihood and Statistical Significance Likelihood, or statistical significance

The probability for the null hypothesis to be true Expressed by a percentage As a convention in the humanities and social sciences, we take 5%

sure that the null hypothesis is true (p = 0.05) as a cut-off point. Greater than 5% sure (p > 0.05), we cannot reject the null hypothesis; less than or equal to 5% sure (p ≤ 0.05), we reject the null hypothesis

(Levon 2010:71)

6 Inferential Statistics – Chi Square Test (1) Related to 2 category type questions The test compares the observed frequencies with the expected

ones, in order to establish whether the null hypothesis is true or false

How to Calculate the observed frequencies Calculate the expected frequencies Calculate the chi squared values Sum the chi squared values up Calculate the degree of freedom If the critical value of significance is higher than the one related to p=0.05,

the null hypotesis will be true

You can use RBRUL or TEST.CHI.QUAD Excel formula

7 Inferential Statistics – Chi Square Test (2) You can use TEST.CHI.QUAD Excel formula Example: occurrences of code-switching in relation to age brackets in

Filipino language survey N.B.: Age as a category type question because we consider age brackets!

8 Inferential Statistics – Chi Square Test (3) Observed frequencies:

=(E3*B5)/E5 in H3 =(E3*C5)/E5 in I3 =(E3*D5)/E5 in J3

9 Inferential Statistics – Chi Square Test (4) Chi Square Test in J5:

=TEST.CHI.QUAD(B3:D3;H3:J3)

The value is > 0.05, therefore the results were achieved by chance (NO STATISTICAL SIGNIFICANCE)

10 Inferential Statistics – Scatterplot

Related to 2 continuous type questions

Compares the correlation between two variables Positive correlation Negative correlation

You can use RBRUL – see slide #56

11 Inferential Statistics – ANOVA

ANalysis Of VAriance Bi/Multivariate Regression Analysis

Related to more than one category type question and more than one continuous type question

You can use RBRUL – see e-book

12 Inferential and multivariate statistics Inferential statistics

Formulating and testing hypothesis Key concepts: likelihood, dependent and independent variables, hypothesis

and null hypothesis

Multivariate statistics, or statistical modelling How a dependant variable changes in relation to two or more independent

variables Key concept: the three lines of evidence (See Tagliamonte 2012)

Statistical significance (p<0.05) Factor weight (FW→1) Strength of factor group

13 Rbrul and multivariate statistics Rbrul

Based on R Tool for multivariate statistics Input: Excel worksheet Output: numbers

What for? Formulating hypothesis after descriptive analysis of a

questionnaire/corpus Testing hypothesis with inferential multivariate analysis

What do we need? Excel worksheet in .csv format R

14Converting .xlsx format to .csv (1)Let’s consider the Filipino language survey (.xls format)1. Go to http://www.docspal.com (or another online converter)

15Converting .xlsx format to .csv (2)2. Upload .xls or .xlsx Excel file and select .csv in “convert to”

16Converting .xlsx format to .csv (3)3. Click on “Convert”

17Converting .xlsx format to .csv (4)4. Click on output file

18Converting .xlsx format to .csv (5)5. Click on “Salva pagina con nome”

19Converting .xlsx format to .csv (6)6. .csv output file

20Rbrul: Installation step-by-step (1)1. Download R: http://cran.r-project.org/bin/windows/base/

21Rbrul: Installation step-by-step (2)2. Press “Avanti” until the installation process finishes.

22Rbrul: Installation step-by-step (3)3. Open R. If you have troubles, right-click “Esegui come amministratore”.

23Rbrul: Installation step-by-step (4)4. Open R.

24Rbrul: Installation step-by-step (5)5. Write: source(“http://www.danielezrajohnson.com/Rbrul.R”)

25Rbrul: Installation step-by-step (6)6. Hit the Enter key

26Rbrul: Installation step-by-step (7)7. Write rbrul()

27Rbrul: Installation step-by-step (8)

8. Hit the Enter key. Now you are in Rbrul.

28 Rbrul: Loading data (1)1. Write 1 and press the Enter key

29 Rbrul: Loading data (2)2. Write c and press the Enter key

30 Rbrul: Loading data (3)3. Open the questionnaire in .csv

31Rbrul: Loading data (4)4. Now you are ready

32 Example: Linguistic survey and RBRUL (1) Considered variables:

Code-switching (category type variable/question)

Who speaks what language(s) at work, with friends, & with family in IT & PH (continuous type question)

Who uses what language(s) when watching TV, reading, dreaming, & thinking (category type question)

Number of known languages (continuous type question)

Age (continuous type question)

33 Example: Linguistic survey and RBRUL (2) Hypothesis:

Code-switching & who speaks what language(s) at work, with friends, & with family in IT & PH (cat+con: bivariate analysis)

Code-switching & Who uses what language(s) when watching TV, reading, dreaming, & thinking (cat+cat: cross tabulation)

Number of known languages & age (con+con: scatterplot)

34

Hypothesis: Code-switching and language use (1)Formulate hypothesis on code-switching and language use with friends

in IT/PH using bivariate analysis.Is there a relation between the number of languages used to talk with friends in PH and in IT & the occurrences of code-switching?Average PH: 1.43Average IT: 1.31

Category+continuous: bivariate analysis

1. Press 5 for bivariate analysis and hit Enter key.

35Hypothesis: Code-switching and language use (2) Formulate hypothesis on code-switching and language use with friends

in IT/PH using bivariate analysis2. Choose variables (1)

36Hypothesis: Code-switching and language use (3) Formulate hypothesis on code-switching and language use with friends

in IT/PH using bivariate analysis3. Dependant variable (50)

37Hypothesis: Code-switching and language use (4) Formulate hypothesis on code-switching and language use with friends

in IT/PH using bivariate analysis4. Type of response (Enter)

38Hypothesis: Code-switching and language use (5) Formulate hypothesis on code-switching and language use with friends

in IT/PH using bivariate analysis5. Choose application (2 + Enter x3)

39Hypothesis: Code-switching and language use (6) Formulate hypothesis on code-switching and language use with friends

in IT/PH using bivariate analysis6. Choose independent variable (# lang used with Friends in IT/PH) (42 Enter 46 Enter x2)

40Hypothesis: Code-switching and language use (7) Formulate hypothesis on code-switching and language use with friends

in IT/PH using bivariate analysis7. Choose continuous variable (42 Enter 46 Enter x2)

41Hypothesis: Code-switching and language use (8) Formulate hypothesis on code-switching and language use with friends

in IT/PH using bivariate analysis8. Modelling (5 Enter)

42Hypothesis: Code-switching and language use (9) Formulate hypothesis on code-switching and language use with friends

in IT/PH using bivariate analysis8. Modelling (5 Enter)

43Hypothesis: Code-switching and language use (10)

Formulate hypothesis on code-switching and language use with friends in IT/PH using bivariate analysisLogodd: 0.571 vs 0.292 (If positive, high likelihood)Deviance: 142.818 vs 144.821 (The larger the deviance, the less accurate the result given)P value: 0.0644 vs 0.234 (>0.05)

Therefore: Correlation code-switching/language use with friends is NOT SIGNIFICANT

44 Hypothesis: Code-switching and language use (11)

The same procedure can be adopted in analysing the relation between code-switching & language used with family & at work in Italy and in the Philippines

45Hypothesis: Code-switching and language use – TV (1)

Formulate hypothesis on code-switching and language use when watching TV using cross tabulation and Chi Square Test.Is there a relation between the languages used to watch TV & the occurrences of code-switching?

Category+category: cross tabulation1. Press 4 for cross tabulation and hit Enter key.

46Hypothesis: Code-switching and language use – TV (2)

Formulate hypothesis on code-switching and language use when watching TV using cross tabulation and Chi Square Test.2. Choose factors for columns (50 Enter)

47Hypothesis: Code-switching and language use – TV (3)

Formulate hypothesis on code-switching and language use when watching TV using cross tabulation and Chi Square Test.3. Choose factors for rows (51 Enter x3)

48Hypothesis: Code-switching and language use – TV (4)

Formulate hypothesis on code-switching and language use when watching TV using cross tabulation and Chi Square Test.4. Cross tabulation

Do those who watch TV in Italian code-switch more?

49Hypothesis: Code-switching and language use – TV (5)

Formulate hypothesis on code-switching and language use when watching TV using cross tabulation and Chi Square Test.5. Chi Square Test in Excel Effective frequency of Italian/Code-switching: 45 Expected frequency of Italian/Code-switching: 32.09

Multiply the total amount of observed frequencies related to the first independent variable (=45) and the total amount of observed frequencies related to its dependent variable (=87). The amount is then divided by the total amount of the frequencies (=122).

𝐸𝑥𝑝 . 𝑓𝑟𝑒𝑞 .=87∗45122 =𝟑𝟐 .𝟎𝟗

50Hypothesis: Code-switching and language use – TV (6)

Formulate hypothesis on code-switching and language use when watching TV using cross tabulation and Chi Square Test.5. Chi Square Test in Excel

51Hypothesis: Code-switching and language use – TV (7)

Formulate hypothesis on code-switching and language use when watching TV using cross tabulation and Chi Square Test.5. Degree of freedom: (3-1)*(8-1)=2*7=14

0.1863 is the result of chi.sq.tst. The value referred to p=0,05 is 1.761. Our result is much lower. (p>0.40!)Therefore: there can’t be a relationship c.s/watching tv in other languages.

52Hypothesis: Age and number of known languages (1)

Formulate hypothesis on age and number of known languages using scatterplot.Is there a relation between the number of known languages & age?

Continuous+continuous: scatterplot1. Press 6 for scatterplot and hit Enter key.

53Hypothesis: Age and number of known languages (2)

Formulate hypothesis on age and number of known languages using scatterplot.2. Press 1 to enter scatterplot menu and select y-axis variable (2 Enter)

54Hypothesis: Age and number of known languages (3)

Formulate hypothesis on age and number of known languages using scatterplot.3. Press 12 to enter scatterplot menu and select x-axis variable (12 Enter)

55Hypothesis: Age and number of known languages (4)

Formulate hypothesis on age and number of known languages using scatterplot.4. Select standard layout and features (Enter x8)

56Hypothesis: Age and number of known languages (5)

Formulate hypothesis on age and number of known languages using scatterplot.5. Scatterplot appears

57

Hypothesis: Age and number of known languages (6) Formulate hypothesis on age and number of known languages using scatterplot.

The line is higher at the beginning and lower at the end: Negative relation

The elder the people, the higer the amount of known languages?YES, because of negative correlation

58 To sum up1. Descriptive analysis – Hypothesis → Null Hypothesis

1 continuous + 1 category type question: comparison of means 2 category type questions: crosstabs 2 continuous type questions: scatterplot

2. Inferential analysis – Null hypothesis test → Significance 1 continuous + 1 category type question: bi/multivariate analysis (ANOVA) 2 category type questions: cross tabulation + chi squared test 2 continuous type questions: correlation

59References

BLOOMER A. & WRAY A., 2006, Projects in Linguistics 2nd Edition, Hodder Arnold, London and New York. HON, K., 2013, “An Introduction to Statistics”, retrievable from the World Wide Web: http://www.artofproblemsolving.com/LaTeX/Examples/statistics_firstfive.pdfJOHNSON, D. E., 2009, “Getting off the GoldVarb Standard: Introducing Rbrul for Mixed-Effects Variable Rule Analysis”, in Language and Linguistics Compass 3/1 (2009): 359–383TAGLIAMONTE, S. A., 2012, “Quantitative Analysis”, in TAGLIAMONTE S. A., 2012, Change, Observation, Interpretation, Wiley Blackwell, Chichester TAMMINGA, M., 2011, “Getting started with Rbrul”, retrievable from the World Wide Web: http://www.danielezrajohnson.com/Getting_started_with_Rbrul.pdf SUNDERLAND J., 2010, "Research Questions in Linguistics", in Litosseliti L. (ed.), Research Methods in Linguistics, Continuum, London and New York: 9-28.

See e-book in my blog

60

Thank you